
from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     np.ndarray		,    _lowerCamelCase					:     np.ndarray		,    _lowerCamelCase					:     np.ndarray		,    _lowerCamelCase					:     int		,    _lowerCamelCase					:     int)   ->       np.ndarray:






							'''simple docstring'''





							__UpperCamelCase      :  List[str]       =   cva.getAffineTransform(_lowerCamelCase		,    _lowerCamelCase)
							return cva.warpAffine(_lowerCamelCase		,    _lowerCamelCase		,    (rows, cols))


if __name__ == "__main__":
		# read original image
		lowercase    :   Tuple						=			cva.imread(
		    str(Path(__file__).resolve().parent.parent / 'image_data' / 'lena.jpg')
		)
		# turn image in gray scale value
		lowercase    :   Tuple						=			cva.cvtColor(image, cva.COLOR_BGR2GRAY)
		# get image shape
		lowercase				,     lowercase    :   Optional[int]						=			gray_img.shape

		# set different points to rotate image
		lowercase    :   Tuple						=			np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
		lowercase    :   Union[str, Any]						=			np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
		lowercase    :   int						=			np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
		lowercase    :   str						=			np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

		# add all rotated images in a list
		lowercase    :   Optional[Any]						=			[
		    gray_img,
		    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
		    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
		    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
		]

		# plot different image rotations
		lowercase    :   Optional[int]						=			plt.figure(1)
		lowercase    :   Dict						=			['Original', 'Rotation 1', 'Rotation 2', 'Rotation 3']
		for i, image in enumerate(images):
				plt.subplot(2, 2, i + 1), plt.imshow(image, 'gray')
				plt.title(titles[i])
				plt.axis('off')
				plt.subplots_adjust(left=0.0, bottom=0.0_5, right=1.0, top=0.9_5)
		plt.show()

import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


lowercase    :   List[str]						=			logging.get_logger(__name__)




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	def __init__(   self						:Dict	,  *a						:Tuple	,  **a						:List[Any]		)						->					None:
								warnings.warn(
								    "The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
								    " Please use PerceiverImageProcessor instead."	,  a	,  )
								super().__init__(*a	,  **a		)